Results 261 to 270 of about 3,667,438 (313)

Principal component regression, ridge regression and ridge principal component regression in spectroscopy calibration

Journal of Chemometrics, 1997
Ridge regression (RR) and principal component regression (PCR) are two popular methods intended to overcome the problem of multicollinearity which arises with spectral data. The present study compares the performances of RR and PCR in addition to ordinary least squares (OLS) and partial least squares (PLS) on the basis of two data sets.
Evelyne Vigneau
exaly   +3 more sources

Kernel Ridge Regression-Based Graph Dataset Distillation

Knowledge Discovery and Data Mining, 2023
The huge volume of emerging graph datasets has become a double-bladed sword for graph machine learning. On the one hand, it empowers the success of a myriad of graph neural networks (GNNs) with strong empirical performance.
Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, H. Tong   +6 more
semanticscholar   +1 more source

Dimension free ridge regression

Annals of Statistics, 2022
Random matrix theory has become a widely useful tool in high-dimensional statistics and theoretical machine learning. However, random matrix theory is largely focused on the proportional asymptotics in which the number of columns grows proportionally to ...
Chen Cheng, A. Montanari
semanticscholar   +1 more source

High Precision Error Prediction Algorithm Based on Ridge Regression Predictor for Reversible Data Hiding

IEEE Signal Processing Letters, 2021
An efficient predictor is crucial for high embedding capacity and low image distortion. In this letter, a ridge regression-based high precision error prediction algorithm for reversible data hiding is proposed.
Xiaoyu Wang, Xingyuan Wang, Bin Ma, Qi Li, Y. Shi   +4 more
semanticscholar   +1 more source

Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression

Reliability Engineering & System Safety, 2021
Intelligent fault diagnosis of gearbox holds important implications for the safety assessment and risk analysis of rotating machinery. Due to many monitoring variables in engineering practice, it is often necessary to install multiple sensors to monitor ...
Xin Li, Xiang Zhong, Haidong Shao, Te Han, Changqing Shen   +4 more
semanticscholar   +1 more source

Detection of influential observations in ridge regression and modified ridge regression

Model Assisted Statistics and Applications, 2012
The detection of influential observations is important because of their unduly large influence on the regression analysis results. Numerous diagnostics on identifying these observations are developed in the regression analysis. Pena's statistic is one of the proposed diagnostics. In this study, Pena's approach is formulated to ridge regression (RR) and
Semra Türkan, Öniz Toktamis
openaire   +1 more source

Beta ridge regression estimators: simulation and application

Communications in statistics. Simulation and computation, 2021
The beta regression model is commonly used when analyzing data that come in the form of rates or percentages. However, a problem that may encounter when analyzing these kinds of data that has not been investigated for this model is the multicollinearity ...
M. Abonazel, I. M. Taha
semanticscholar   +1 more source

Ridge regression neural network for pediatric bone age assessment

Multimedia tools and applications, 2021
Bone age is an important measure for assessing the skeletal and biological maturity of children. Delayed or increased bone age is a serious concern for pediatricians, and needs to be accurately assessed in a bid to determine whether bone maturity is ...
Ibrahim Salim, A. Hamza
semanticscholar   +1 more source

On the Saturation Effect of Kernel Ridge Regression

International Conference on Learning Representations
The saturation effect refers to the phenomenon that the kernel ridge regression (KRR) fails to achieve the information theoretical lower bound when the smoothness of the underground truth function exceeds certain level.
Yicheng Li, Haobo Zhang, Qian Lin
semanticscholar   +1 more source

The Comparison Of Partial Least Squares Regression, Principal Component Regression And Ridge Regression With Multiple Linear Regression For Predicting Pm10 Concentration Level Based On Meteorological Parameters

, 2021
Air pollution shows itself as a serious problem in big cities in Turkey, especially for winter seasons. Particulate atmospheric pollution in urban areas is considered to have significant impact on human health.
E. Polat, Süleyman Günay
semanticscholar   +1 more source